An electrooculogram is the electric potential measured around the eyes, which is generated by the corneo-retinal standing potential between the front and back of the eye. Pairs of electrodes are generally attached either to the left and right of the eyes (horizontal electrooculography component) or above and below the eye (vertical electrooculography component) to measure the eye movements. The horizontal and vertical electrooculography (EOG) components are then obtained by subtracting the signal obtained at one electrode from the signal at the other electrode. Electrooculography (EOG) signals acquire different types of eye movements, which can be employed for human-machine interfaces (HMI) and also for diagnostic purposes. Electrooculography (EOG) signals tend to be contaminated with noise due to unconstrained head movements. This head movement noise or artifact degrades the signal quality as well as increases the misclassification rate of eye movement detection. General filtering and preprocessing techniques are unable to remove this noise. Many traditional systems and methods have previously focused on the signal clarity but none of them have specifically focused on removing the head movement artifacts from the electrooculography signals.
Researchers generally carry out experiments in controlled lab environments, under constrained conditions so as to minimize any sort of contamination of the electrooculography (EOG) signals. Various factors may affect the electrooculography (EOG) signals quality which include power line noise, facial electromyography (EMG), loose electrode contact, and also head movement artifacts. Most of these artifacts can be removed by simple band pass, median, and/or moving average filtering. However the artifacts due to the head movements, in absence of chin rest or constraints of not moving the head, poses to be more problematic as it is in the same frequency range of electrooculography (EOG) signals and also morphologically close to electrooculography (EOG). Researchers have worked on removal of power line, blinks, and facial electromyography (EMG) noise from the electrooculography (EOG). To the best of authors' knowledge none of the existing works have concentrated on presence of head-movement noise in electrooculography (EOG) signals and in turn removal of the same.
The artifacts due to the head movements, in absence of chin rest or constraints of not moving the head, poses to be problematic as it is in the same frequency range of electrooculography (EOG) signals and also morphologically close to electrooculography (EOG). Further, the electrooculography (EOG) signals contaminated with head movement noise tend to misclassification rate of eye movement recognition. Hence, there is a need for a technology that reduces the effect of head movement artifacts and thus to improve the classification accuracy of eye movement detection from electrooculography (EOG) signals.